There are 14 repositories under deep-learning-visualization topic.
Neat (Neural Attention) Vision, is a visualization tool for the attention mechanisms of deep-learning models for Natural Language Processing (NLP) tasks. (framework-agnostic)
Training and evaluating state-of-the-art deep learning CNN architectures for plant disease classification task.
🏔️ Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
Attribution (or visual explanation) methods for understanding video classification networks. Demo codes for WACV2021 paper: Towards Visually Explaining Video Understanding Networks with Perturbation.
Notebooks for Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
My Notes on Deep Learning 💫
Visualize the convergence of complex roots with different optimizers.
📉 Visualize your Deep Learning training in static graphics
Data for Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Pure Swift TensorBoard plugin for DL4S
FitsBook Python Library. Tool for generating real-time machine learning training statistics and storing model histories. Direct integration with Keras Framework.
An abstract deep learning training framework.
MNIST classifier with a graphical user interface and a canvas for drawing the digits, doing classifying in real time
A simple simple version of tensorboard implemented by d3.js
Fitsbook React WebApp. Tool for generating real-time machine learning training statistics and storing model histories. Direct integration with Keras.